Richard McKinley

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Canonical proof nets for classical logic

Richard McKinley, Richard McKinley, 2012, Ann. Pure Appl. Log..

Pooling-Free Fully Convolutional Networks with Dense Skip Connections for Semantic Segmentation, with Application to Brain Tumor Segmentation

Richard McKinley, Mauricio Reyes, Alain Jungo, 2017, BrainLes@MICCAI.

Stratify or Inject: Two Simple Training Strategies to Improve Brain Tumor Segmentation.

Richard McKinley, Mauricio Reyes, Raphael Meier, 2019, 1907.12941.

Simultaneous lesion and neuroanatomy segmentation in Multiple Sclerosis using deep neural networks pdf

Richard McKinley, Andrew Chan, Mauricio Reyes, 2019, ArXiv.

Categories and Subject Descriptors: F4.1 [Mathematical logic and formal languages]: Mathematical

Richard McKinley, Richard McKinley, 2022 .

High-Resolution Continuous Scan Acoustical Holography Applied to High-Speed Jet Noise

Wright Patterson, Richard McKinley, Philip J. Morris, 2010 .

A Machine Learning Approach to Perfusion Imaging With Dynamic Susceptibility Contrast MR

Fabien Scalzo, Richard McKinley, Roland Wiest, 2018, Front. Neurol..

Triplanar 3D-to-2D networks with dense connections and dilated convolutions: application to the KITS 2019 challenge

Richard McKinley, Roland Wiest, Hendrik von Tengg-Kobligk, 2019 .

3D-LZ Flight Test of 2013: Landing an EH-60L Helicopter in a Brownout Degraded Visual Environment

James Savage, U. S. Air Force, Zoltan Szoboszlay, 2014 .

An Algorithmic Interpretation of a Deep Inference System

Richard McKinley, Kai Brünnler, Richard McKinley, 2008, LPAR.

Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation

Richard McKinley, Raphael Meier, Roland Wiest, 2018, BrainLes@MICCAI.

Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence

Richard McKinley, Andrew Chan, Mauricio Reyes, 2019, NeuroImage: Clinical.

Adolescent Brain Cognitive Development Neurocognitive Prediction: First Challenge, ABCD-NP 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings

Richard McKinley, Mauricio Reyes, Roland Wiest, 2019, ABCD-NP@MICCAI.

Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction

Víctor M. Pérez-García, Richard McKinley, Mauricio Reyes, 2017, BrainLes@MICCAI.

Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning

Fabien Scalzo, Richard McKinley, Andreas Hess, 2018, BrainLes@MICCAI.

The alpha-epsilon calculus

Richard McKinley, 2009 .

Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

Simon Andermatt, Simon Pezold, Sang Hyun Park, 2019, IEEE Transactions on Medical Imaging.

Segmenting the Ischemic Penumbra: A Decision Forest Approach with Automatic Threshold Finding

Levin Häni, Richard McKinley, Mauricio Reyes, 2015, Brainles@MICCAI.

The Reduction of Advanced Military Aircraft Noise

James Bridges, Richard McKinley, Philip J. Morris, 2011 .

Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation

Richard McKinley, Raphael Meier, Roland Wiest, 2019, BrainLes@MICCAI.

Improving labeling efficiency in automatic quality control of MRSI data

Richard McKinley, Roland Wiest, Johannes Slotboom, 2017, Magnetic resonance in medicine.

Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks pdf

Richard McKinley, Mauricio Reyes, Christian Rummel, 2019, ArXiv.

Nabla-net: A Deep Dag-Like Convolutional Architecture for Biomedical Image Segmentation

Tom Gundersen, Richard McKinley, Andrew Chan, 2016, BrainLes@MICCAI.

Soft Linear Set Theory

Richard McKinley, 2008, J. Log. Algebraic Methods Program..

Enhancing interpretability of automatically extracted machine learning features: application to a RBM‐Random Forest system on brain lesion segmentation

Victor Alves, Richard McKinley, Mauricio Reyes, 2018, Medical Image Anal..

Expansion Nets: Proof-Nets for Propositional Classical Logic

Richard McKinley, Richard McKinley, 2010, LPAR.

Surface-Based Brain Morphometry for the Prediction of Fluid Intelligence in the Neurocognitive Prediction Challenge 2019

Richard McKinley, Mauricio Reyes, Roland Wiest, 2019, ABCD-NP@MICCAI.

Noise Reduction Efforts for Special Operations C-130 Aircraft Using Active Synchrophaser Control

Richard McKinley, Bill Hale, Daryl Hammond, 1998 .

Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient pdf

Spyridon Bakas, Hongwei Li, Bjoern H. Menze, 2021, ArXiv.

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results pdf

Christos Davatzikos, Gowtham Krishnan Murugesan, Chandan Ganesh, 2021, ArXiv.

Pooling-free fully convolutional networks with dense skip connections for semantic segmentation , with application to segmentation of white matter lesions

Richard McKinley, Mauricio Reyes, Alain Jungo, 2017 .

Automatic quality control in clinical 1H MRSI of brain cancer

Richard McKinley, Roland Wiest, Urspeter Knecht, 2016, NMR in biomedicine.

Segmenting the ischemic penumbra: a spatial Random Forest approach with automatic threshold finding

Levin Häni, Richard McKinley, Mauricio Reyes, 2015 .

Relevance of the cerebral collateral circulation in ischaemic stroke: time is brain, but collaterals set the pace.

Richard McKinley, Roland Wiest, David Liebeskind, 2017, Swiss medical weekly.